| 中国区域降水偏差订正的初步研究 |
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| 引用本文： | 张海鹏,智协飞,吉璐莹.中国区域降水偏差订正的初步研究[J].气象科学,2020,40(4):467-474. |
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| 作者姓名： | 张海鹏 智协飞 吉璐莹 |
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| 作者单位： | 南京信息工程大学 气象灾害预报预警与评估协同创新中心/气象灾害教育部重点实验室, 南京 210044;南京信息工程大学 气象灾害预报预警与评估协同创新中心/气象灾害教育部重点实验室, 南京 210044;南京大气科学联合研究中心, 南京 210008 |
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| 基金项目： | 国家自然科学基金资助项目（41575104）；NJCAR重点项目（NJCAR2016ZD04） |
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| 摘 要： | 基于中国气象局公共气象服务中心提供的降水预报资料,利用频率匹配法和阈值法对2015年全年的降水预报进行偏差订正并对订正后的结果进行检验。结果表明:(1)偏差订正可显著减少集成系统降水预报的小雨空报现象,改善"有雨或无雨"的定性预报性能,提高集成系统的晴雨预报准确率。(2)订正后降水量级大小更接近实况降水,并且集成系统预报的平均绝对误差和面积偏差(干偏差或湿偏差)均有所降低。(3)偏差订正对降水预报的改善程度与系统本身预报性能有关,系统本身预报误差越大,订正效果越好。
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| 关 键 词： | 偏差订正 降水预报 频率匹配法 阈值法 降水检验 |
| 收稿时间： | 2019/1/4 0:00:00 |
A preliminary study on calibration in precipitation forecast over China |
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| ZHANG Haipeng,ZHI Xiefei,JI Luying.A preliminary study on calibration in precipitation forecast over China[J].Scientia Meteorologica Sinica,2020,40(4):467-474. |
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| Authors: | ZHANG Haipeng ZHI Xiefei JI Luying |
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| Institution: | Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters/Key Laboratory of Meteorological Disaster, Ministry of Education, Nanjing University of Information Science & Technology, Nanjing 210044, China;Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters/Key Laboratory of Meteorological Disaster, Ministry of Education, Nanjing University of Information Science & Technology, Nanjing 210044, China;Nanjing Joint Center for Atmospheric Research, Nanjing 210008, China |
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| Abstract: | Based on the rainfall data taken from the Public Meteorological Service Center, China Meteorological Administration (CMA), the calibration of the precipitation forecast is performed by using Frequency Matching Method (FMM) and the threshold method. Then the performance of calibration is evaluated by Mean Absolute Error (MAE), Test Score (TS), etc. The results in the whole 2015 show that: (1) the calibration can significantly reduce the occurrence of false alarms of light rain and improve the qualitative forecast for a "rain or no rain" event. (2) The calibrated precipitation forecasts are much closer to the observation, and the MAE and area bias (dry bias or wet bias) of the ensemble system are also greatly reduced. (3) The improvement by the calibration method is related to the forecasting performance of the ensemble system itself. The greater the forecast errors, the better the calibrated forecast skill. |
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| Keywords: | calibration precipitation forecast frequency matching method threshold precipitation verification |
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